Incorporation of probabilistic seismic phase labels into a Bayesian multiple-event seismic locator

Abstract

We add probabilistic phase labels to the multiple-event joint probability function of Myers et al. that formerly included event locations, traveltime corrections and arrival-time measurement precision. Prior information on any of the multiple-event parameters may be used. The phase-label model includes a null label that captures phases not belonging to the collection of phases under consideration. Using the Markov-Chain Monte Carlo method, samples are drawn from the multiple-event joint probability function to infer the posteriori distribution that is consistent with priors and the arrival-time data set. Using this approach phase-label error can be accessed and phase-label error is propagated to all other multiple-event parameters. We test the method using a ground-truth data set of nuclear explosions at the Nevada Test Site. We find that posteriori phase labels agree with the meticulously analysed data set in more than 97 per cent of instances and the results are robust even when the input phase-label information is discarded. Only when a large percentage of the arrival-time data are corrupted does prior phase label information improve resolution of multiple-event parameters. Simultaneous modelling of the entire multiple-event system results in accurate posteriori probability regions for each multiple-event parameter.